"""simple docstring"""



import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__:str									=			logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__:int									=			{
    """microsoft/git-base""": """https://huggingface.co/microsoft/git-base/resolve/main/config.json""",
}






class  snake_case__      (       snake_case_       ):
 _snake_case       :					List[str]							  =						"""git_vision_model"""


 def __init__( self    ,		lowerCamelCase=768    ,		lowerCamelCase=3072    ,		lowerCamelCase=12    ,		lowerCamelCase=12    ,		lowerCamelCase=3    ,		lowerCamelCase=224    ,		lowerCamelCase=16    ,		lowerCamelCase="quick_gelu"    ,		lowerCamelCase=1E-5    ,		lowerCamelCase=0.0    ,		lowerCamelCase=0.02    ,		**lowerCamelCase    ,		):
        super().__init__(**lowerCamelCase						)

        __a       =    hidden_size
        __a       =    intermediate_size
        __a       =    num_hidden_layers
        __a       =    num_attention_heads
        __a       =    num_channels
        __a       =    patch_size
        __a       =    image_size
        __a       =    initializer_range
        __a       =    attention_dropout
        __a       =    layer_norm_eps
        __a       =    hidden_act






 @classmethod
 def 						a__   ( cls    ,		lowerCamelCase    ,		**lowerCamelCase						):
        cls._set_token_in_kwargs(lowerCamelCase						)

        __a ,   __a       =    cls.get_config_dict(lowerCamelCase    ,		**lowerCamelCase						)

        # get the vision config dict if we are loading from GITConfig
        if config_dict.get("model_type"						) == "git":
               __a       =    config_dict["vision_config"]

        if "model_type" in config_dict and hasattr(cls    ,		"model_type"						) and config_dict["model_type"] != cls.model_type:
               logger.warning(
                   F"You are using a model of type {config_dict['model_type']} to instantiate a model of type "
                   F"{cls.model_type}. This is not supported for all configurations of models and can yield errors."						)

        return cls.from_dict(lowerCamelCase    ,		**lowerCamelCase						)






class  snake_case__      (       snake_case_       ):
 _snake_case       :					Union[str, Any]							  =						"""git"""


 def __init__( self    ,		lowerCamelCase=None    ,		lowerCamelCase=30522    ,		lowerCamelCase=768    ,		lowerCamelCase=6    ,		lowerCamelCase=12    ,		lowerCamelCase=3072    ,		lowerCamelCase="gelu"    ,		lowerCamelCase=0.1    ,		lowerCamelCase=0.1    ,		lowerCamelCase=1024    ,		lowerCamelCase=0.02    ,		lowerCamelCase=1E-12    ,		lowerCamelCase=0    ,		lowerCamelCase="absolute"    ,		lowerCamelCase=True    ,		lowerCamelCase=False    ,		lowerCamelCase=101    ,		lowerCamelCase=102    ,		lowerCamelCase=None    ,		**lowerCamelCase    ,		):
        super().__init__(bos_token_id=lowerCamelCase    ,		eos_token_id=lowerCamelCase    ,		pad_token_id=lowerCamelCase    ,		**lowerCamelCase						)

        if vision_config is None:
               __a       =    {}
               logger.info("vision_config is None. initializing the GitVisionConfig with default values."						)

        __a       =    GitVisionConfig(**lowerCamelCase						)
        __a       =    vocab_size
        __a       =    hidden_size
        __a       =    num_hidden_layers
        __a       =    num_attention_heads
        __a       =    hidden_act
        __a       =    intermediate_size
        __a       =    hidden_dropout_prob
        __a       =    attention_probs_dropout_prob
        __a       =    max_position_embeddings
        __a       =    initializer_range
        __a       =    layer_norm_eps
        __a       =    position_embedding_type
        __a       =    use_cache
        __a       =    tie_word_embeddings
        __a       =    num_image_with_embedding

        __a       =    bos_token_id
        __a       =    eos_token_id






 def 						a__   ( self						):
        __a       =    copy.deepcopy(self.__dict__						)
        __a       =    self.vision_config.to_dict()
        __a       =    self.__class__.model_type
        return output

"""simple docstring"""



from __future__ import annotations

from math import pi



def 	_lowerCamelCase(	a   ,    a   ,    a				):

       if (inductance, frequency, reactance).count(0				) != 1:
              raise ValueError("One and only one argument must be 0"				)
       if inductance < 0:
              raise ValueError("Inductance cannot be negative"				)
       if frequency < 0:
              raise ValueError("Frequency cannot be negative"				)
       if reactance < 0:
              raise ValueError("Inductive reactance cannot be negative"				)
       if inductance == 0:
              return {"inductance": reactance / (2 * pi * frequency)}
       elif frequency == 0:
              return {"frequency": reactance / (2 * pi * inductance)}
       elif reactance == 0:
              return {"reactance": 2 * pi * frequency * inductance}
       else:
              raise ValueError("Exactly one argument must be 0"				)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
